DNA Methylation In Samples Research Articles

Novel bioinformatic analyses of somatic cell contamination in sperm samples

The assessment of epigenetic profiles in sperm is sensitive to somatic cell contamination, which can influence methylation signals at gene promoters. This contamination is particularly problematic in the assessment of DNA methylation in samples with low sperm counts, where fractional amounts of somatic cell DNA can lead to significant shifts in measured methylation state. In this study, a new method of detecting possible somatic cell contamination is proposed through two multi-region bioinformatic models: a traditional differential methylation analysis and a machine learning logistic regression model. These models were trained on publicly available sperm (n = 489) and blood (n = 1029) DNA methylation array data and tested on a contamination set, wherein the sperm of four donors with normal sperm counts were run on a 450k methylation array with four permutations each, including pure blood, half blood and half sperm by DNA concentration, half blood and half sperm by cell count, and pure sperm (n = 16). The DMR and logistic regression model classified the contamination testing set with 100% and 94% accuracy, respectively. These new methods of detecting the effects of somatic cell contamination allow for more accurate differentiation between epigenetic profiles that contain a biological somatic-like shift and those that have somatic-like signatures because of contamination.

Heterogeneity of increased biological age in type 2 diabetes correlates with differential tissue DNA methylation, biological variables, and pharmacological treatments.

Biological age (BA) closely depicts age-related changes at a cellular level. Type 2 diabetes mellitus (T2D) accelerates BA when calculated using clinical biomarkers, but there is a large spread in the magnitude of individuals' age acceleration in T2D suggesting additional factors contributing to BA. Additionally, it is unknown whether BA can be changed with treatment. We hypothesized that potential determinants of the heterogeneous BA distribution in T2D could be due to differential tissue aging as reflected at the DNA methylation (DNAm) level, or biological variables and their respective therapeutic treatments. Publicly available DNAm samples were obtained to calculate BA using the DNAm phenotypic age (DNAmPhenoAge) algorithm. DNAmPhenoAge showed age acceleration in T2D samples of whole blood, pancreatic islets, and liver, but not in adipose tissue or skeletal muscle. Analysis of genes associated with differentially methylated CpG sites found a significant correlation between eight individual CpG methylation sites and gene expression. Clinical biomarkers from participants in the NHANES 2017-2018 and ACCORD cohorts were used to calculate BA using the Klemera and Doubal (KDM) method. Cardiovascular and glycemic biomarkers associated with increased BA while intensive blood pressure and glycemic management reduced BA to CA levels, demonstrating that accelerated BA can be restored in the setting of T2D.

Large-scale placenta DNA methylation integrated analysis reveals fetal sex-specific differentially methylated CpG sites and regions

Although male–female differences in placental structure and function have been observed, little is understood about their molecular underpinnings. Here, we present a mega-analysis of 14 publicly available placenta DNA methylation (DNAm) microarray datasets to identify individual CpGs and regions associated with fetal sex. In the discovery dataset of placentas from full term pregnancies (N = 532 samples), 5212 CpGs met genome-wide significance (p < 1E−8) and were enriched in pathways such as keratinization (FDR p-value = 7.37E−14), chemokine activity (FDR p-value = 1.56E−2), and eosinophil migration (FDR p-value = 1.83E−2). Nine differentially methylated regions were identified (fwerArea < 0.1) including a region in the promoter of ZNF300 that showed consistent differential DNAm in samples from earlier timepoints in pregnancy and appeared to be driven predominately by effects in the trophoblast cell type. We describe the largest study of fetal sex differences in placenta DNAm performed to date, revealing genes and pathways characterizing sex-specific placenta function and health outcomes later in life.

Reliability of a novel approach for reference-based cell type estimation in human placental DNA methylation studies

The placenta is a central organ during early development, influencing trajectories of health and disease. DNA methylation (DNAm) studies of human placenta improve our understanding of how its function relates to disease risk. However, DNAm studies can be biased by cell type heterogeneity, so it is essential to control for this in order to reduce confounding and increase precision. Computational cell type deconvolution approaches have proven to be very useful for this purpose. For human placenta, however, an assessment of the performance of these estimation methods is still lacking. Here, we examine the performance of a newly available reference-based cell type estimation approach and compare it to an often-used reference-free cell type estimation approach, namely RefFreeEWAS, in placental genome-wide DNAm samples taken at birth and from chorionic villus biopsies early in pregnancy using three independent studies comprising over 1000 samples. We found both reference-free and reference-based estimated cell type proportions to have predictive value for DNAm, however, reference-based cell type estimation outperformed reference-free estimation for the majority of data sets. Reference-based cell type estimations mirror previous histological knowledge on changes in cell type proportions through gestation. Further, CpGs whose variation in DNAm was largely explained by reference-based estimated cell type proportions were in the proximity of genes that are highly tissue-specific for placenta. This was not the case for reference-free estimated cell type proportions. We provide a list of these CpGs as a resource to help researchers to interpret results of existing studies and improve future DNAm studies of human placenta.

Abstract 13580: DNA Methylation of Skeletal Muscle Tissue in Patients With Hypertension and Diabetes Undergoing Cardiopulmonary Bypass

Introduction: Epigenomic changes may affect the condition of patients before and after surgery. The epigenome-wide DNA methylation profiling of human skeletal muscle (SKM) specimens obtained from patients undergoing cardiac surgery utilizing cardiopulmonary bypass (CPB) was examined. Hypothesis: We hypothesized that regulatory changes in SKM that develop in patients with HTN and DM include epigenetic regulation and aimed to characterize the epigenome-wide signature of these changes, both at baseline and after cardiac surgery. Methods: SKM was obtained from the internal mammary artery bed before and after termination of cardiopulmonary bypass. Specimens of patients without hypertension or diabetes (control), those with hypertension alone (BP ≥ 130), those with hypertension combined with either controlled (HbA1C &lt;=7) or poorly controlled (HbA1C &gt; 7) diabetes were examined. SKM DNA methylation was profiled via Illumina MethylationEpic arrays and analyzed by principal component analysis, cluster analysis and analysis of variance followed by network and pathway analysis. Results: DNA methylation in samples from patients with hypertension and diabetes was significantly different in 5822 loci for controlled diabetes and in 7177 loci for uncontrolled diabetes; hypertension alone produced minimal effect. These loci produced a tightly interacting network with 560 hubs and 7055 edges. These loci were associated with genes involved in pathways of IL-1, IL-12, IL-18, TNFα; IFNγ and VEGF signaling, in NF-κB and Wnt pathways, apoptosis and DNA damage response. SKM at the end of CPB revealed 282 highly significant loci or 193,567 loci with lower significance and the magnitude of the effect not exceeding 10-20%. Conclusions: Preoperatively, patients with diabetes show substantial change in SKM DNA methylation epigenome wide. Compared to diabetes, hypertension did not as substantially influence the methylome in the SKM. During surgery multiple low-grade methylation changes occur that may mask the effects of the disease; moreover in a few loci more prominent changes occur that may be part of a compensatory/regulatory response to surgery utilizing CPB.

The Functional DNA Methylation Signatures Relevant to Altered Immune Response of Neonatal T Cells with l-Arginine Supplementation

l-Arginine is an important nutrient in the infant diet that significantly regulates the maturation of the immune system in neonates, including the maturation of CD4+ T cells. The biological activities of CD4+ T cells differ substantially between neonates and adults, and these differences may be governed by epigenetic processes. Investigating these differences and the causative processes may help understand neonatal and developmental immunity. In this study, we compared the functional DNA methylation profiles in CD4+ T cells of neonates and adults, focusing on the role of l-arginine supplementation. Umbilical cord blood and adult CD4+ T cells were cultured with/without l-arginine treatment. By comparing DNA methylation in samples without l-arginine treatment, we found that CD4+ T cells of neonatal cord blood generally showed higher DNA methylation than those of adults (average CpG methylation percentage 0.6305 for neonate and 0.6254 for adult, t-test p-value < 0.0001), suggesting gene silencing in neonates. By examining DNA methylation patterns of CpG dinucleotides induced by l-arginine treatment, we found that more CpG dinucleotides were hypomethylated and more genes appeared to be activated in neonatal T-cells as compared with adult. Genes activated by l-arginine stimulation of cord blood samples were more enriched regarding immune-related pathways. CpG dinucleotides at IL-13 promoter regions were hypomethylated after l-arginine stimulation. Hypomethylated CpG dinucleotides corresponded to higher IL-13 gene expression and cytokine production. Thus, DNA methylation partially accounts for the mechanism underlying differential immune function in neonates. Modulatory effects of l-arginine on DNA methylation are gene-specific. Nutritional intervention is a potential strategy to modulate immune function of neonates.

MethylCC: technology-independent estimation of cell type composition using differentially methylated regions

A major challenge in the analysis of DNA methylation (DNAm) data is variability introduced from intra-sample cellular heterogeneity, such as whole blood which is a convolution of DNAm profiles across a unique cell type. When this source of variability is confounded with an outcome of interest, if unaccounted for, false positives ensue. Current methods to estimate the cell type proportions in whole blood DNAm samples are only appropriate for one technology and lead to technology-specific biases if applied to data generated from other technologies. Here, we propose the technology-independent alternative: methylCC, which is available at https://github.com/stephaniehicks/methylCC.

DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

BackgroundPerinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology.ResultsGenome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression.ConclusionsMany of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

DNA epigenetic signature predictive of benefit from neoadjuvant chemotherapy in oesophageal adenocarcinoma: results from the MRC OE02 trial

BackgroundDNA methylation signatures describing distinct histological subtypes of oesophageal cancer have been reported. We studied DNA methylation in samples from the MRC OE02 phase III trial, which randomised patients with resectable oesophageal cancer to surgery alone (S) or neoadjuvant chemotherapy followed by surgery (CS). AimThe aim of the study was to identify epigenetic signatures predictive of chemotherapy benefit in patients with oesophageal adenocarcinoma (OAC) from the OE02 trial and validate the findings in an independent cohort. MethodsDNA methylation was analysed using the Illumina GoldenGate platform on surgically resected OAC specimens from patients in the OE02 trial. Cox proportional hazard analysis was performed to select probes predictive of survival in the CS arm. Non-negative matrix factorisation was used to perform clustering and delineate DNA methylation signatures. The findings were validated in an independent cohort of patients with gastroesophageal adenocarcinoma treated with neoadjuvant chemotherapy. ResultsA total of 229 patients with OAC were analysed from the OE02 trial (118 in the CS arm and 111 in the S arm). There was no difference in DNA methylation status between the CS and S arms. A metagene signature was created by dichotomising samples into two clusters. In cluster 1, patients in the CS arm had significant overall survival (OS) benefit (median OS CS: 931 days vs. S: 536 days [HR: 1.54, P = 0.031]). In cluster 2, patients in the CS arm had similar (or worse) OS compared with patients in the S arm (CS: 348 days vs. S: 472 days [HR: 0.70, P = 0.1], and test of interaction was significant (p = 0.005). In the validation cohort (n = 13), there was no difference in DNA methylation status in paired pre- and post-treatment samples. When the epigenetic signature was applied, cluster 1 samples had better OS (median OS, cluster 1: 1174 days vs. cluster 2: 392 days, HR: 3.47, p = 0.059) ConclusionsThis is the first and largest study of DNA methylation in patients with OAC uniformly treated in a randomised phase III trial. We identified an epigenetic signature that may serve as a predictive biomarker for chemotherapy benefit in OAC.

Eating Disorders and Epigenetics.

Eating disorders (EDs) are characterized by intense preoccupation with shape and weight and maladaptive eating practices. The complex of symptoms that characterize EDs often arise through the activation of latent genetic potentials by environmental exposures, and epigenetic mechanisms are believed to link environmental exposures to gene expression. This chapter provides an overview of genetic factors acting in the etiology of EDs. It then provides a background to the hypothesis that epigenetic mechanisms link stresses such as obstetric complications and childhood abuse as well as effects of malnutrition to eating disorders (EDs). The chapter then summarizes the emerging body of literature on epigenetics and EDs-mainly studies on DNA methylation in samples of anorexia and bulimia. The available evidence base suggests that an epigenetically informed perspective contributes in valuable ways to the understanding of why people develop EDs.

Shared genetic control of expression and methylation in peripheral blood.

BackgroundExpression QTLs and epigenetic marks are often employed to provide an insight into the possible biological mechanisms behind GWAS hits. A substantial proportion of the variation in gene expression and DNA methylation is known to be under genetic control. We address the proportion of genetic control that is shared between these two genomic features.ResultsAn exhaustive search for pairwise phenotypic correlations between gene expression and DNA methylation in samples from human blood (n = 610) was performed. Of the 5 × 109 possible pairwise tests, 0.36 % passed Bonferroni corrected p-value cutoff of 9.9 × 10-12. We determined that the correlation structure between probe pairs was largely due to blood cell type specificity of the expression and methylation probes. Upon adjustment of the expression and methylation values for observed blood cellular composition (n = 422), the number of probe pairs which survived Bonferroni correction reduced by more than 5400 fold. Of the 614 correlated probe pairs located on the same chromosome, 75 % share at least one methylation and expression QTL at nominal 10-5p-value cutoff. Those probe pairs are located within 1Mbp window from each other and have a mean of absolute value of genetic correlation equal to 0.69, further demonstrating the high degree of shared genetic control.ConclusionsOverall, this study demonstrates notable genetic covariance between DNA methylation and gene expression and reaffirms the importance of correcting for cell-counts in studies on non-homogeneous tissues.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2498-4) contains supplementary material, which is available to authorized users.

RSPH9 methylation pattern as a prognostic indicator in patients with non-muscle invasive bladder cancer.

DNA methylation is a frequent and early epigenetic event with potential application as a biomarker for cancer detection and an indicator of disease evolution. The aim of the present study was to identify novel methylation markers for the prediction of patient outcomes using microarray analysis of DNA methylation in samples from long-term follow-up patients with non-muscle invasive bladder cancer (NMIBC). Candidate methylation markers were selected from our previously published genome-wide methylation profiles. The clinical relevance of candidate methylation markers was determined by quantitative pyrosequencing analysis of 136 human bladder specimens (8 normal controls and 128 NMIBCs). The reversibility of DNA methylation was examined by 5-Aza-CdR treatment in human bladder cancer cell lines. The methylation patterns of candidate markers were significantly associated with aggressive clinicopathological features. In multivariate regression analysis, hypermethylation of radial spoke head 9 homolog (RSPH9) was an independent predictor of disease recurrence (hazard ratio, 3.02; P=0.001) and progression (hazard ratio, 8.25; P=0.028). The methylation level of RSPH9 decreased with 5-Aza-CdR treatment and progressively increased in its absence in bladder cancer cell lines. RSPH9 methylation is an independent prognostic indicator in NMIBC patients, and could be of value for the assessment of disease recurrence and progression and for clinical decision-making regarding treatment.

Discovery of epigenetic biomarkers for the noninvasive diagnosis of fetal disease

The primary goal of this study was to identify CpG sites in the human genome that are differentially methylated in DNA obtained from chorionic villus sampling (CVS) samples and gestational age-matched maternal blood cell (MBC) samples. We used the HumanMethylation27 DNA Analysis BeadChip to characterize DNA methylation in samples of CVS and MBC. We then selected a subset of differentially methylated CpG sites on chromsome 13 and subjected them to analysis by mass spectrometry using the Epityper platform. We identified 718 tissue-specific differentially methylated regions (DMRs) between MBC and CVS; 563 of these were hypermethylated in MBC and hypomethylated in CVS, whereas 155 sites were hypomethylated in MBC and hypermethylated in CVS. Further analysis of 13 DMRs on chromosome 13 by Epityper confirmed the microarray data and provided us with additional data about the methylation patterns of surrounding CpG sites. Analysis of the resulting data identified a large number of cytosine-guanine dinucleotides that are potential biomarkers for the selective amplification of fetal DNA from maternal plasma and the subsequent noninvasive detection of trisomy 13.

Aberrant DNA methylation of tumor‐related genes in oral rinse

The early detection of oral squamous cell carcinoma (OSCC) is important, and a screening test with high sensitivity and specificity is urgently needed. Therefore, in this study, the authors investigated the methylation status of tumor-related genes with the objective of establishing a noninvasive method for the detection of OSCC. Oral rinse samples were obtained from 34 patients with OSCC and from 24 healthy individuals (controls). The methylation status of 13 genes was determined by using methylation-specific polymerase chain reaction analysis and was quantified using a microchip electrophoresis system. Promoter methylation in each participant was screened by receiver operating characteristic analysis, and the utility of each gene's methylation status, alone and in combination with other genes, was evaluated as a tool for oral cancer detection. Eight of the 13 genes had significantly higher levels of DNA methylation in samples from patients with OSCC than in controls. The genes E-cadherin (ECAD), transmembrane protein with epidermal growth factor-like and 2 follistatin-like domains 2 (TMEFF2), retinoic acid receptor beta (RARβ), and O-6 methylguanine DNA methyltransferase (MGMT) had high sensitivity (>75%) and specificity for the detection of oral cancer. OSCC was detected with 100% sensitivity and 87.5% specificity using a combination of ECAD, TMEFF2, RARβ, and MGMT and with 97.1% sensitivity and 91.7% specificity using a combination of ECAD, TMEFF2, and MGMT. The aberrant methylation of a combination of marker genes present in oral rinse samples was used to detect OSCC with >90% sensitivity and specificity. The detection of methylated marker genes from oral rinse samples has great potential for the noninvasive detection of OSCC.

Acquired TNFRSF14 Mutations in Follicular Lymphoma Are Associated with Worse Prognosis

Clinical correlative studies have linked 1p36 deletions with worse prognosis in follicular lymphoma (FL). In this study, we sought to identify the critical gene(s) in this region that is responsible for conferring inferior prognosis. BAC array technology applied to 141 FL specimens detected a minimum region of deletion (MRD) of ∼97 kb within 1p36.32 in 20% of these cases. Frequent single-nucleotide polymorphism-detected copy-neutral loss of heterozygosity was also found in this region. Analysis of promoter CpGs in the MRD did not reveal differential patterns of DNA methylation in samples that differed in 1p36 status. Exon sequencing of MRD genes identified somatic alterations in the TNFRSF14 gene in 3 of 11 selected cases with matching normal DNA. An expanded cohort consisting of 251 specimens identified 46 cases (18.3%) with nonsynonymous mutations affecting TNFRSF14. Overall survival (OS) and disease-specific survival (DSS) were associated with the presence of TNFRSF14 mutation in patients whose overall treatment included rituximab. We further showed that inferior OS and DSS were most pronounced in patients whose lymphomas contained both TNFRSF14 mutations and 1p36 deletions after adjustment for the International Prognostic Index [hazard ratios of 3.65 (95% confidence interval, 1.35-9.878, P=0.011) and 3.19 (95% confidence interval, 1.06-9.57, P=0.039), respectively]. Our findings identify TNFRSF14 as a candidate gene associated with a subset of FL, based on frequent occurrence of acquired mutations and their correlation with inferior clinical outcomes.

Detection of Aberrant DNA Methylation in Acute Lymphocytic Leukemia (ALL) Using a Real-Time Polymerase Chain Reaction (PCR) Assay.

Aberrant DNA methylation of promoter-associated CpG islands is a frequent event in ALL. DNA methylation of specific subsets of genes is associated with poor prognosis and is stable in a majority of patients (pts) at the time of relapse (Clinical Cancer Res 2002; 8:1897), and therefore tracking these epigenetic marks during remission may predict for relapse risk. Most commonly used methods to detect DNA methylation exploit the availability of sodium bisulfite that transforms unmethylated C into A/T leaving methylated C as such. This has allowed the development of several techniques that use conventional PCR or sequencing to detect methylated alleles. Although there are significant differences in the sensitivity and specificity of these assays, with bisulfite sequencing considered the gold standard, most of them are labor intensive and require several days to be performed. To circumvent some of these problems, we have developed a real-time bisulfite PCR assay to detect methylation of p57KIP2, p73, and p15 in samples obtained from bone marrows in pts with ALL at remission. Methylation of these genes has been shown to be common in ALL and to predict for poor prognosis at initial presentation (Blood 2003; 101:4131). This method allows for the simultaneous analysis of multiple samples in less than 24 hours, is quantitative, and requires less than 0.2μg of DNA for each target gene. To amplify bisulfite treated DNA, we designed primer sets and probes for all three genes in regions known to be inversely correlated with gene expression. To quantify methylation density, we used the interferon γ (INFG) gene as an internal control because it has very rare CpG sites, is a single copy gene and has no homology with other known genes. Methylation density is defined as: Methylation (%) = 2CT of target gene / 2 CT of EFM x 100. CT is the number of cycles threshold, and EFM the estimated 100% fully methylation (EFM) of the target gene in control experiments. Using DNA artificially methylated with SssI in dilution experiments with unmethylated DNA, p57, p15 and p73 methylation density could be detected at dilutions of 0.2%, 1.2% and 0.1%, respectively. We then studied the methylation status of 30 cell lines (22 hematopoietic and 8 no-hematopoietic). Methylation of p57, p15 and p73 gene was detected in 17(57%), 19(63%) and 16(53%) cell lines respectively. Methylation of 3 genes, 2 genes and 1 gene was observed in 9(30%), 8(27%) and 7(23%) cell lines respectively. DNA methylation of p15 and p73 was not detected in the marrow from 6 healthy volunteers but p15 was detected (0.1% methylation) in 1 out of 6 of these specimens. Subsequently, we studied 50 pts with ALL at the time of remission. We found the frequencies of p57, p15 and p73 gene to be 2(4%), 26(52%) and 10(20%), respectively. There was a trend towards a better overall survival for pts with methylation of 0 or 1 gene (209 weeks) compared with those with methylation of 2 or more genes (71 weeks), p=0.1. In conclusion, the real-time bisulfite PCR described here allows for the rapid detection of aberrant DNA methylation in samples obtained at the time of remission in pts with ALL and may have a role in the development of techniques to assess minimal residual disease in this group of pts.